Yong Ge
Biographic Data
| ID | 3635624 |
|---|---|
| NAME | Yong Ge |
| GIVEN NAMES | Yong |
| FAMILY NAME | Ge |
| SIGNATURE | GE Y |
| AFFILIATIONS | Chinese Academy of Sciences |
| ORCID | 0000-0002-9524-7908 |
| VERIFIED | Yes |
| TOTAL WORKS | 26 |
| TOTAL CITATIONS | 21 |
| WORKS AS AUTHOR | 26 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Micro-CT reveals a delayed trajectory of rice domestication in the south China coast
The interaction between prehistoric humans and plant resources is key to understanding the origin and spread of agriculture. As a pivotal region for the transmission of East Asian continental cultures to the islands of Southeast Asia, the trajectory of rice ( Oryza sativa ) cultivation along the South China coast continues to be debated, largely due to the lack of direct evidence. This study employs micro-CT scanning to analyze Neolithic pottery …
Integrating cannabis into the prehistoric crop assemblage
Evolutionary modeling reveals that value-oriented knowledge creation behaviors reinvent jobs
Recently, the strong artificial intelligence-based augmented capability enables the autonomous completion of traditional jobs devoid of human intervention, impacting labor markets. However, the underlying mechanisms have not been explored enough in prior research. In this research, we propose a computational model, focusing on the interplay between world knowledge networks and organizational knowledge sets, along with external labor market condit…
Association between frailty transitions and chronic lung disease incidence
The association between changes in frailty status and the prevalence of chronic lung diseases (CLD) is critical. This study aims to explore the relationship between variations in frailty status and incidence of CLD. This study utilized data from four national prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), Health and Retirement Study (HRS) and Survey of Health, Ageing and …
Exploring Spatial Stratified Heterogeneity for Local Geometry Structures
Geometry structure modeling plays an increasingly important role in the era of artificial-intelligence-guided geoscience discovery. It poses challenges in detecting and quantifying spatial stratified heterogeneity, which is critical in capturing causal association and developing stratum-specific models in geoscience, as up-to-date methods mainly focus on value disparities and leave the corresponding spatial geometry structure aside. This article …
Earliest known well‐preserved flour comestibles unearthed in the Wupu Cemetery in Hami, Xinjiang, China
Exploring the utilisation of flour in ancient Xinjiang is crucial for understanding the use of different grain crops as staple comestibles. In this study, multiple analyses were applied to identify five flour food remnants discovered in the Wupu Cemetery (1100–400 BCE) in Hami, Xinjiang. Results show that two of the samples were comprised of broomcorn millet ( Panicum miliaceum ) mixed with wheat ( Triticum aestivum ) and barley ( Hordeum spp.), …
Scaling Geospatial Data from the Perspective of Complexity
A fundamental challenge in geospatial data science is to determine how a property, or its characterization, changes with a change in the scale of measurement. Except for geostatistical regularization of the variogram, which is theoretically well established, the scaling behaviors of a wide range of alternative measures of spatial association remain unclear. This limits the ability to make inferences at scales beyond the scale of measurement. The …
After the pandemic
The COVID-19 lockdowns have transitioned to a new normal and triggered commodity supply disruption and trade uncertainty, yet little is known about the seafood trade resilience of developing and developed countries amid pandemic-related shocks. Here, employing a newly developed geographical transition-net model, we simulate a set of idealized lockdown scenarios in a real-world seafood network. The results show that (1) even if restrictions from r…
Data-Driven Models Informed by Spatiotemporal Mobility Patterns for Understanding Infectious Disease Dynamics
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accuracy and consistency. Our proposed data-driven approach integrates spatiotemporal human mobility patterns from detailed point-of-interest clustering and population flow data. These patterns inform th…
The Spatial Effects of Regional Poverty
Recognizing the spatial effects of regional poverty is essential for achieving sustainable poverty alleviation. This study investigates these spatial effects and their determinants across three distinct administrative levels within Hubei Province, China. To analyze the spatial patterns and heterogeneity of multi-scale regional poverty, we employed various spatial analysis techniques, including the global and local Moran’s I statistics, the Linema…
Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model
Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urbanization trends. The existing GDP spatial models often rely on prediction residuals for model evaluation or utilize residual distribution to improve the final accuracy, frequently overlooking the…
Combined and delayed impacts of epidemics and extreme weather on urban mobility recovery
The ever-increasing pandemic and natural disasters might spatial-temporal overlap to trigger compound disasters that disrupt urban life, including human movements. In this study, we proposed a framework for data-driven analyses on mobility resilience to uncover the compound effects of COVID-19 and extreme weather events on mobility recovery across cities with varied socioeconomic contexts. The concept of suppression risk (SR) is introduced to qua…
Micro‐CT‐assisted determination of the shattering and non‐shattering phenotypes of charred rice spikelet bases from archaeological sites
The selection of a non‐shattering phenotype is a pivotal change in the process of rice domestication. However, current research is heavily restricted by the preservation conditions of macro‐plant remains in early and middle Neolithic sites, as very limited well‐preserved rice spikelet bases could be retrieved. We present a non‐destructive method based on micro‐computed tomographic (CT) scanning, which could provide detailed visualization of the i…
Spatial Association from the Perspective of Mutual Information
Measures of spatial association are important to reveal the spatial structures and patterns in geographical phenomena. They have utility for spatial interpolation, stochastic simulation, and causal inference, among others. Such measures are abundantly available for continuous spatial variables, whereas for categorical spatial variables they are less well developed. In this research, we developed a measure of spatial association for categorical sp…
Information Consistency-Based Measures for Spatial Stratified Heterogeneity
As a typical form of spatial heterogeneity, spatial stratified heterogeneity is widely observed in geographical phenomena. Although the q statistic provides a measure of spatial stratified heterogeneity using variance differences, it is not suitable for nominal target variables and neglects information differences between strata at higher order moments. Based on the mutual information and relative entropy between variables, two spatial stratified…
Who and which regions are at high risk of returning to poverty during the Covid-19 pandemic
Pandemics such as COVID-19 and their induced lockdowns/travel restrictions have a significant impact on people’s lives, especially for lower-income groups who lack savings and rely heavily on mobility to fulfill their daily needs. Taking the COVID-19 pandemic as an example, this study analysed the risk of returning to poverty for low-income households in Hubei Province in China as a result of the COVID-19 lockdown. Employing a dataset including i…
Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression
Spatial heterogeneity is important for exploring data relationships between real estate price and its influential factors. The geographically weighted regression (GWR) technique has been frequently adopted for this purpose. In this study, we collected a second-hand real estate house price data set of Wuhan, in which each property is located the same as the community it belongs to. Thus, this data set possesses a typical characteristic, that is, d…
Unraveling the association between the urban polycentric structure and urban surface thermal environment in urbanizing China
An improved hidden Markov model-based map matching algorithm considering candidate point grouping and trajectory connectivity
The hidden Markov model-based map matching algorithm (HMM-MM) is an effective method for online vehicle navigation and offline trajectory position correction. Common HMM-MMs are susceptible to the influence of adjacent road segment endpoints and similar parallel roads, because the multi-index probability model may ignore some indexes when the probability of other indexes is high. This makes the map-matching result not meet the assumption that veh…
Understanding the Relationship between Dominant Geo-Environmental Factors and Rural Poverty in Guizhou, China
Geo-environmental factors are believed to be major determinants of rural poverty. However, few studies have quantified the effects of these factors on rural poverty in China. In this paper, we used county-level poverty incidence data and geo-environmental factors to explore spatial patterns of the incidence of poverty using global and local spatial autocorrelation analysis and to investigate the effect of geo-environment factors on rural poverty …
Effect of different resumption strategies to flatten the potential Covid-19 outbreaks amid society reopens
Business resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases
An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis
Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discret…
Land Use and Land Cover Change Modeling and Future Potential Landscape Risk Assessment Using Markov-CA Model and Analytical Hierarchy Process
Land use and land cover change (LULCC) has directly played an important role in the observed climate change. In this paper, we considered Dujiangyan City and its environs (DCEN) to study the future scenario in the years 2025, 2030, and 2040 based on the 2018 simulation results from 2007 and 2018 LULC maps. This study evaluates the spatial and temporal variations of future LULCC, including the future potential landscape risk (FPLR) area of the 200…
Phytolith analysis for the identification of barnyard millet (Echinochloa sp.) and its implications
Response of phytoliths in Phragmites communis to elevated CO2 concentration in Songnen Grassland, China
Phytolith analysis for the identification of barnyard millet (Echinochloa sp.) and its implications
Spatial Association from the Perspective of Mutual Information
Measures of spatial association are important to reveal the spatial structures and patterns in geographical phenomena. They have utility for spatial interpolation, stochastic simulation, and causal inference, among others. Such measures are abundantly available for continuous spatial variables, whereas for categorical spatial variables they are less well developed. In this research, we developed a measure of spatial association for categorical sp…
Information Consistency-Based Measures for Spatial Stratified Heterogeneity
As a typical form of spatial heterogeneity, spatial stratified heterogeneity is widely observed in geographical phenomena. Although the q statistic provides a measure of spatial stratified heterogeneity using variance differences, it is not suitable for nominal target variables and neglects information differences between strata at higher order moments. Based on the mutual information and relative entropy between variables, two spatial stratified…
Scaling Geospatial Data from the Perspective of Complexity
A fundamental challenge in geospatial data science is to determine how a property, or its characterization, changes with a change in the scale of measurement. Except for geostatistical regularization of the variogram, which is theoretically well established, the scaling behaviors of a wide range of alternative measures of spatial association remain unclear. This limits the ability to make inferences at scales beyond the scale of measurement. The …
An improved hidden Markov model-based map matching algorithm considering candidate point grouping and trajectory connectivity
The hidden Markov model-based map matching algorithm (HMM-MM) is an effective method for online vehicle navigation and offline trajectory position correction. Common HMM-MMs are susceptible to the influence of adjacent road segment endpoints and similar parallel roads, because the multi-index probability model may ignore some indexes when the probability of other indexes is high. This makes the map-matching result not meet the assumption that veh…
Adaptive modeling of the human-environment relationship applied to estimation of the population carrying capacity in an earthquake zone
Response of phytoliths in Phragmites communis to elevated CO2 concentration in Songnen Grassland, China
Phytolith analysis for the identification of barnyard millet (Echinochloa sp.) and its implications
An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis
Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discret…
Land Use and Land Cover Change Modeling and Future Potential Landscape Risk Assessment Using Markov-CA Model and Analytical Hierarchy Process
Land use and land cover change (LULCC) has directly played an important role in the observed climate change. In this paper, we considered Dujiangyan City and its environs (DCEN) to study the future scenario in the years 2025, 2030, and 2040 based on the 2018 simulation results from 2007 and 2018 LULC maps. This study evaluates the spatial and temporal variations of future LULCC, including the future potential landscape risk (FPLR) area of the 200…
Understanding the Relationship between Dominant Geo-Environmental Factors and Rural Poverty in Guizhou, China
Geo-environmental factors are believed to be major determinants of rural poverty. However, few studies have quantified the effects of these factors on rural poverty in China. In this paper, we used county-level poverty incidence data and geo-environmental factors to explore spatial patterns of the incidence of poverty using global and local spatial autocorrelation analysis and to investigate the effect of geo-environment factors on rural poverty …
Effect of different resumption strategies to flatten the potential Covid-19 outbreaks amid society reopens
Business resumption strategies have the potential to eliminate COVID-19 outbreaks amid society reopening without special control measures. The proposed resumption strategies focused mainly on decreasing the number of imported exposure cases, guaranteeing medical support for epidemic control, or decreasing active cases
Who and which regions are at high risk of returning to poverty during the Covid-19 pandemic
Pandemics such as COVID-19 and their induced lockdowns/travel restrictions have a significant impact on people’s lives, especially for lower-income groups who lack savings and rely heavily on mobility to fulfill their daily needs. Taking the COVID-19 pandemic as an example, this study analysed the risk of returning to poverty for low-income households in Hubei Province in China as a result of the COVID-19 lockdown. Employing a dataset including i…
Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression
Spatial heterogeneity is important for exploring data relationships between real estate price and its influential factors. The geographically weighted regression (GWR) technique has been frequently adopted for this purpose. In this study, we collected a second-hand real estate house price data set of Wuhan, in which each property is located the same as the community it belongs to. Thus, this data set possesses a typical characteristic, that is, d…
Unraveling the association between the urban polycentric structure and urban surface thermal environment in urbanizing China
An improved hidden Markov model-based map matching algorithm considering candidate point grouping and trajectory connectivity
The hidden Markov model-based map matching algorithm (HMM-MM) is an effective method for online vehicle navigation and offline trajectory position correction. Common HMM-MMs are susceptible to the influence of adjacent road segment endpoints and similar parallel roads, because the multi-index probability model may ignore some indexes when the probability of other indexes is high. This makes the map-matching result not meet the assumption that veh…
After the pandemic
The COVID-19 lockdowns have transitioned to a new normal and triggered commodity supply disruption and trade uncertainty, yet little is known about the seafood trade resilience of developing and developed countries amid pandemic-related shocks. Here, employing a newly developed geographical transition-net model, we simulate a set of idealized lockdown scenarios in a real-world seafood network. The results show that (1) even if restrictions from r…
Data-Driven Models Informed by Spatiotemporal Mobility Patterns for Understanding Infectious Disease Dynamics
Data-driven approaches predict infectious disease dynamics by considering various factors that influence severity and transmission rates. However, these factors may not fully capture the dynamic nature of disease transmission, limiting prediction accuracy and consistency. Our proposed data-driven approach integrates spatiotemporal human mobility patterns from detailed point-of-interest clustering and population flow data. These patterns inform th…
The Spatial Effects of Regional Poverty
Recognizing the spatial effects of regional poverty is essential for achieving sustainable poverty alleviation. This study investigates these spatial effects and their determinants across three distinct administrative levels within Hubei Province, China. To analyze the spatial patterns and heterogeneity of multi-scale regional poverty, we employed various spatial analysis techniques, including the global and local Moran’s I statistics, the Linema…
Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model
Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urbanization trends. The existing GDP spatial models often rely on prediction residuals for model evaluation or utilize residual distribution to improve the final accuracy, frequently overlooking the…
Combined and delayed impacts of epidemics and extreme weather on urban mobility recovery
The ever-increasing pandemic and natural disasters might spatial-temporal overlap to trigger compound disasters that disrupt urban life, including human movements. In this study, we proposed a framework for data-driven analyses on mobility resilience to uncover the compound effects of COVID-19 and extreme weather events on mobility recovery across cities with varied socioeconomic contexts. The concept of suppression risk (SR) is introduced to qua…
Micro‐CT‐assisted determination of the shattering and non‐shattering phenotypes of charred rice spikelet bases from archaeological sites
The selection of a non‐shattering phenotype is a pivotal change in the process of rice domestication. However, current research is heavily restricted by the preservation conditions of macro‐plant remains in early and middle Neolithic sites, as very limited well‐preserved rice spikelet bases could be retrieved. We present a non‐destructive method based on micro‐computed tomographic (CT) scanning, which could provide detailed visualization of the i…
Spatial Association from the Perspective of Mutual Information
Measures of spatial association are important to reveal the spatial structures and patterns in geographical phenomena. They have utility for spatial interpolation, stochastic simulation, and causal inference, among others. Such measures are abundantly available for continuous spatial variables, whereas for categorical spatial variables they are less well developed. In this research, we developed a measure of spatial association for categorical sp…
Information Consistency-Based Measures for Spatial Stratified Heterogeneity
As a typical form of spatial heterogeneity, spatial stratified heterogeneity is widely observed in geographical phenomena. Although the q statistic provides a measure of spatial stratified heterogeneity using variance differences, it is not suitable for nominal target variables and neglects information differences between strata at higher order moments. Based on the mutual information and relative entropy between variables, two spatial stratified…
Earliest known well‐preserved flour comestibles unearthed in the Wupu Cemetery in Hami, Xinjiang, China
Exploring the utilisation of flour in ancient Xinjiang is crucial for understanding the use of different grain crops as staple comestibles. In this study, multiple analyses were applied to identify five flour food remnants discovered in the Wupu Cemetery (1100–400 BCE) in Hami, Xinjiang. Results show that two of the samples were comprised of broomcorn millet ( Panicum miliaceum ) mixed with wheat ( Triticum aestivum ) and barley ( Hordeum spp.), …
Scaling Geospatial Data from the Perspective of Complexity
A fundamental challenge in geospatial data science is to determine how a property, or its characterization, changes with a change in the scale of measurement. Except for geostatistical regularization of the variogram, which is theoretically well established, the scaling behaviors of a wide range of alternative measures of spatial association remain unclear. This limits the ability to make inferences at scales beyond the scale of measurement. The …
Evolutionary modeling reveals that value-oriented knowledge creation behaviors reinvent jobs
Recently, the strong artificial intelligence-based augmented capability enables the autonomous completion of traditional jobs devoid of human intervention, impacting labor markets. However, the underlying mechanisms have not been explored enough in prior research. In this research, we propose a computational model, focusing on the interplay between world knowledge networks and organizational knowledge sets, along with external labor market condit…
Association between frailty transitions and chronic lung disease incidence
The association between changes in frailty status and the prevalence of chronic lung diseases (CLD) is critical. This study aims to explore the relationship between variations in frailty status and incidence of CLD. This study utilized data from four national prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), Health and Retirement Study (HRS) and Survey of Health, Ageing and …
Exploring Spatial Stratified Heterogeneity for Local Geometry Structures
Geometry structure modeling plays an increasingly important role in the era of artificial-intelligence-guided geoscience discovery. It poses challenges in detecting and quantifying spatial stratified heterogeneity, which is critical in capturing causal association and developing stratum-specific models in geoscience, as up-to-date methods mainly focus on value disparities and leave the corresponding spatial geometry structure aside. This article …
Micro-CT reveals a delayed trajectory of rice domestication in the south China coast
The interaction between prehistoric humans and plant resources is key to understanding the origin and spread of agriculture. As a pivotal region for the transmission of East Asian continental cultures to the islands of Southeast Asia, the trajectory of rice ( Oryza sativa ) cultivation along the South China coast continues to be debated, largely due to the lack of direct evidence. This study employs micro-CT scanning to analyze Neolithic pottery …
Geography (15 works) · Mathematics (10 works) · Computer Science (9 works) · Statistics (9 works) · Biology (8 works) · China (8 works) · Land Use and Ecosystem Services (8 works) · Ecology (7 works) · Economics (7 works) · Spatial analysis (6 works)